1. Field of the Invention
The invention relates generally to the field of medicine and more specifically to machines and processes for monitoring heart instability.
2. Background Art
Heart rhythm disorders are extremely common in the United States, and cause significant mortality and morbidity. However, there are few methods to predict future rhythm disorders (“arrhythmias”) before they occur. Instead, physicians rely upon detecting the actual rhythm disturbance, which precludes early detection and possible prevention of these disorders. Many methods currently used also may have serious side-effects. Over 2 million Americans suffer from Atrial Fibrillation (AF), a rhythm disorder of the atria (top heart chambers) that causes serious symptoms, lost days from work, and potentially death (Chugh, Blackshear et al. 2001). Sadly, AF sometimes is first detected after it has caused a serious side-effect such as a stroke. Predicting the future development of AF in an individual can prevent such catastrophic events. However, clinical practice is so rudimentary in this area that it relies upon observing episodes of AF to detect future risk, yet many episodes of AF are still missed or misclassified (Chugh, Blackshear et al. 2001). Therefore, prediction of AF has been difficult.
The same problems exist for predicting a variety of important heart instabilities. Sudden cardiac arrest is the leading cause of mortality in the U.S., taking over 300,000 lives per year, largely due to the rhythm disorders of ventricular tachycardia (VT) or fibrillation (VF) (Myerburg and Castellanos 2006). Current methods of predicting future VT/VF are inadequate. In fact, risk is often not identified until after sudden cardiac arrest (SCA) occurs—despite the fact that an individual's chance for surviving out-of-hospital SCA is <10% (Robertson 2000). The inability to predict future VT/VF also leads to a potential overuse of preventive therapy in the form of the implantable cardioverter defibrillators (Myerburg and Castellanos 2006).
The field is replete with attempts to detect these disorders. For instance, it has been shown that human AF, VT and VF, as well as other less serious heart rhythm disorders, can arise by the mechanism of reentry (Kuo, Munakata et al. 1983). In this case, barriers (known as “conduction blocks”) can develop and cause otherwise orderly electrical impulses to disorganize into electrical waves that circulate around the barrier. In addition, localized regions of scar tissue or ischemic tissue propagate electrical activity (depolarization) slower than normal tissue, causing “slow conduction,” which may factor into formation of these wavelets. This may lead to errant, circular propagation. Further, “reentry” or “circus motion” may result, which disrupts depolarization and contraction of the atria or ventricles, and leads to abnormal rhythms (“arrhythmias”). Many tools have been developed to predict rhythm disorders from these large-scale effects, with suboptimal results.
AF often occurs in patients in whom the atria, the top chamber of the heart, is enlarged or weakened. However, whether the AF is the cause or effect of the atrial cardiomyopathy (“heart failure of the atrium”) has been unclear.
In one study (Narayan, Bode et al. 2002b), it is shown that action potential oscillations during atrial flutter (a different abnormal heart rhythm) may enable the transition to AF. However, action potential oscillations during atrial flutter occur in only a small minority of sufferers with AF. In addition, the study observed only the right atrium. However, the left atrium is critical in the initiation of AF, and is the chamber in which treatment for AF is most effective (Calkins et al., 2007). Action potential fluctuations also arise in the left atrium near the pulmonary veins, which leads to AF in a large number of cases (Calkins et al, 2007).
Previous studies from patients with atrial cardiomyopathy undergoing surgery revealed tissue specimens that showed atrium enlargement, weakening of atrial wall contractions, thickening of atrial walls, and cell loss and destruction in cases of cardiomyopathy of the atrium (Frustaci, Chimenti et al. 1997). Often, but not always, these signs are secondary to disease of the ventricles. However, testing using tissue specimens is not a viable clinical tool. Taking tissue from the heart (biopsy) is a risky procedure that may potentially cause serious side-effects including death. In the atrium, this is almost never performed unless a patient is proceeding to surgery for another reason.
Echocardiography can show weakening of contraction and enlargement of the atrium. However, this does not specifically indicate any disease. In fact, weakening can be seen in individuals without primary atrial cardiomyopathy or AF, who may have other common and even non-serious diseases of the ventricles including left ventricular hypertrophy from mild high blood pressure (Thomas, Levett et al. 2002). Weakening and fibrosis of the wall of the atrium can slow electrical conduction through its walls. This leads to a prolonged P-wave duration on the surface ECG. Many studies have used this measurement to predict AF (Steinberg, Prystowski et al. 1994), but with modest results because this factor may not be central to all forms of AF (AF can arise in individuals without atrial fibrosis or conduction slowing). As a result, these and related measurements are not often used clinically.
Other methods used to assess atrial function include elevated levels of natriuretic peptides, yet these methods have not been incorporated into clinical practice in humans because their predictive value is also poor (Therkelsen, Groenning et al. 2004). Other methods exist to measure atrial size, including magnetic resonance imaging and other techniques, yet these methods do not correlate with atrial function. As a result, these methods are not used in clinical practice.
Methods that have been proposed to predict AF risk, or track propensity, are non-specific and not often used. Common methods include clinical associations, such as identifying-individuals with thyroxicosis or heart valve disease as having increased risk for AF. Further, individuals with ventricular disease have higher left atrial pressures which may predispose them to developing AF. Such ventricular diseases include simple ones (left ventricular hypertrophy from aging or high blood pressure), and more complex ones (ventricular cardiomyopathy). Other methods include identifying a large left atrial size on imaging (echocardiography, MRI). However, none of these clinical associations accurately identifies which individuals will develop AF, or when.
Other methods have been described that focus on reentrant mechanisms for AF, but are also not used clinically. Steinberg et al. (Steinberg, Zelenkofske et al. 1993a), Klein et al. (Klein, Evans et al. 1995) and others showed that prolonged atrial activity indicates slow conduction which identifies patients at risk for AF. Work by Narayan et al. (Narayan, Bode et al. 2002b) suggested that the presence of alternate beat variations (“alternans”) of the timing, shape or amplitude of the P-wave (or an atrial signal surrogate) predicts AF. However, those studies pertained only to patients with existing atrial flutter (a related rhythm disorder) in the right atrium (that is less important for AF), and used pacing for studying some of the patients. Thus, the studies did not demonstrate results relevant to most patients with AF, who do not have preceding atrial flutter. Other methods include detecting abnormalities of the sinus node rate that may precede AF (Faddis, Narayan et al. 1999), but also have limited predictive value.
Methods directed to preventing heart rhythm disorders propose fast pacing rates for prevention of arrhythmias, such as overdrive pacing (at faster rates than observed naturally in the individual). These methods have had very limited success.
Atrial cardiomyopathy (heart failure of the top chamber of the heart) is a relatively new concept, and is not often diagnosed clinically. As a result, few therapies have been described to treat atrial cardiomyopathy. However, there is increasing interest in methods of improving atrial function.
New evidence suggests that drugs such as angiotensin-receptor antagonists and angiotensin receptor blockers can prevent atrial fibrosis and progression of atrial cardiomyopathy (Wachtell, Lehto et al. 2005). Similar benefits have been shown for beta-receptor antagonists, and also for agents such as HMG co-A reductase inhibitors (Ehrlich, Biliczki et al. 2008). However, these drugs act over years, not acutely, and it is unclear how well they reverse or stabilize atrial cardiomyopathy that has already developed. Further, many of these drug benefits were discovered indirectly in trials designed to examine benefits of the drugs on ventricular function. Thus, it is not clear if the drugs would lead to similar benefits in direct prospective trials, and in the vast majority of patients with atrial cardiomyopathy without ventricular cardiomyopathy. Finally, many anti-arrhythmic drugs used to prevent and treat AF are suboptimal (Ehrlich, Biliczki et al. 2008).
Ventricular cardiomyopathy is currently viewed predominantly from a structural perspective. Therefore, an individual's ventricular disease is tracked by repeated measurement of left ventricular ejection fraction (LVEF) or the ventricular dimension on an echocardiography. This poses several problems. First, the difference between LVEF, for example 30% versus 25%, is of unclear significance in terms of identifying symptoms, treatment, prognosis, or risk for VT/VF. Second, echocardiography or ventriculography are only reproducible for LVEF within broad ranges, and other methods such as radionuclide angiography are more cumbersome. Third, clinical practice does not show significance in day-to-day or week-to-week fluctuations in structural indices.
Current methods to predict the risk for VT/VF are non-specific. As mentioned above, the most common risk factor is the presence of reduced LVEF or heart failure symptoms. However, these methods over-detect at risk individuals by a factor of up to 18:1 (i.e. 18 individuals have to receive prophylactic ICD therapy to save one individual who will actually develop VT/VF) (Myerburg and Castellanos 2006). This method also fails to identify over 50% of all individuals who experience SCA and whose LVEF is not reduced. Thus, these criteria are suboptimal.
Rate response of ventricular action potentials at a slow heart rate (109 beats per minute—within the range expected for only mild exertion such as light walking) do not predict VT/VF. (Narayan et al, 2007): This is consistent with other art (such as U.S. Pat. Nos. 6,915,156 and 7,313,437 by Christini and colleagues) which describes methods to control cardiac alternans in action potential duration by controlling the interval separating beats. These approaches have not translated into the patient care setting.
Other methods proposed to predict VT/VF have had mixed success. Most of these methods focus on presumed reentrant mechanisms, and are indirect. These methods include detecting slow conduction in an ECG (signal averaged ECG) that may indicate a predisposition to reentry (Cain, Anderson et al. 1996a). Work by Kleiger et al. (Kleiger, Millar et al. 1987) shows that reduced 24 hour variability in the interval between heart beats (“heart rate variability”) predicts VT or VF. A related method examines heart rate variability after premature beats (Schmidt, Malik et al. 1999). In a related method, abnormal innervation of the ventricle assessed using nuclear imaging may identify risk for VT/VF (Arora, Ferrick et al. 2003b). U.S. Pat. No. 4,802,481 issued to Cohen (Cohen and Smith 1989) and work by others (Smith, Clancy et al. 1988a; Rosenbaum, Jackson et al. 1994; Narayan, Lindsay et al. 1999d) describes techniques for assessing myocardial electrical instability as strictly alternate-beat fluctuations in T-wave energy (also known as “T-wave alternans”). Newer methods such as described in U.S. Pat. No. 5,555,888 issued to Brewer (Brewer and Taghizadeh 1996) and work by Marrouche et al. (Marrouche, Pavia et al. 2002), use alterations in the ventricular activation after sub-threshold current to assess the risk for VT or VF. Finally, abnormal delayed enhancement of the ventricle using magnetic resonance imaging may identify risk for VT/VF (Schmidt, Azevedo et al. 2007). For VT and VF, success has been suboptimal for tools that probe the reentry circuit with electrophysiologic study (Buxton, Lee et al. 2000), the signal-averaged ECG to examine slow conduction (Cain, Anderson et al. 1996a), and indices of repolarization including T-wave alternans (Narayan 2006a) and QT dispersion (Brendorp, Elming et al. 2001).
More recent work suggests that nervous activity/innervation can increase the risk for VT/VF (Stein, Domitrovich et al. 2005) and for AF (Patterson, Po et al. 2005). However, the mechanism linking autonomic activity with arrhythmias is unclear—particularly in humans. Of note, none of these techniques are part of implantation planning for cardioverter defibrillators (ACC/AHA/ESC 2006) or are used routinely in the clinic. All have suboptimal predictive value, and therefore tend to be more of a rough guide to risk rather than a predictive tool.
Several approaches have been described to improve ventricular cardiomyopathy. However, none of these methods work in all patient populations, and some failed to reduce VT/VF in tandem with improvements in heart failure (Bradley 2003b). Some drugs have been shown to improve ventricular function in cardiomyopathy. These include angiotensin-receptor antagonists and angiotensin receptor blockers, and beta-receptor antagonists (Poole-Wilson, Swedberg et al. 2003). However, these drugs act over years, rather than acutely.
Over the past decade, it has been shown that cardiac resynchronization therapy also improves ventricular cardiomyopathy in patients with reduced LVEF, heart failure and evidence for delayed activation between ventricles (Abraham, Fisher et al. 2002). However, it remains unclear whether cardiac resynchronization therapy itself improves the aspects of heart failure that lead to VT/VF, which is why many physicians implant an ICD in tandem with a resynchronization device (ACC/AHA/ESC 2006). Placing a pacing lead close to an arrhythmia circuit enables easier termination than if leads are remote from that location (Stevenson, Khan et al. 1993; Morton, Sanders et al. 2002a). However, current studies poorly describe methods of placing a permanent pacemaker or defibrillator lead to reduce VT/VF. Tse et al. (Xu, Tse et al. 2002), Leclercq et al. (LeClercq, Victor et al. 2000), and Meisel et al. (Meisel, Pfeiffer et al. 2001) among others, show that carefully selected ventricular pacing—particularly in the left ventricle—can improve hemodynamics and, based on work by Zagrodzky et al. (Zagrodzky, Ramaswamy et al. 2001), reduce arrhythmia incidence.
Further, it is known that pacing in certain regions of the heart, such as the right ventricle, can lead to right ventricular cardiomyopathy (DAVID 2002). However, many patients do not experience right ventricular cardiomyopathy due to pacing, and physicians still practice right ventricular pacing. However, the only way to determine if the detrimental effect is developing is to examine worsening in LVEF.
In animals, AF or atrial cardiomyopathy is not spontaneous but rather is caused by very rapid pacing or toxic drugs. In animals with experimentally induced atrial fibrillation, one can see evidence of the changes in atrial cardiomyopathy from histology or at the sub-cellular level (Ausma, van der Velden et al. 2003). However, as described above, obtaining tissue samples from human atria in human being is very difficult. Human AF is also different from AF in animal models. Therefore, there exists a need to better detect heart instability in humans.
The following references provide additional background information: Abraham, W. T., et al. (2002), “Cardiac Resynchronization in Chronic Heart Failure”, N Engl J Med. 346:1845-1853; ACC/AHA/ESC (2006). “ACC/AHA/ESC 2006 Guidelines for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death—Executive Summary. A Report of the American College of Cardiology/American Heart Association Task Force and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Develop Guidelines for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death)”, J Am Coll Cardiol 48(5): 1064-1108; Arora, R., et al. (2003b), “1-123 MIBG imaging and heart rate variability analysis to predict the need for an implantable cardioverter defibrillator”, Journal of Nuclear Cardiology 10(2): 121-131; Ausma, J., et al. (2003), “Reverse Structural and Gap-Junctional Remodeling After Prolonged Atrial Fibrillation in the Goat”, Circulation 107(15): 2051-2058; Bloomfield, D. M., et al. (2002). “Interpretation and Classification of Microvolt T-Wave Alternans Tests”, J. Cardiovasc Electrophysiol. 13(5): 502-512; Bradley, D. J. (2003b), “Combining Resynchronization and Defibrillation Therapies for Heart Failure”, JAMA 289(20): 2719; Brendorp, B., et al. (2001), “QT Dispersion Has No Prognostic Information for Patients With Advanced Congestive Heart Failure and Reduced Left Ventricular Systolic Function”, Circulation 103: 831-5; Brewer, J. E. and E. Taghizadeh, U.S. Pat. No. 5,555,888, “Method for automatic, adaptive, active facilitation to access myocardial electrical instability”; Bristow, M. R., et al. (2004), “Cardiac-Resynchronization Therapy with or without an Implantable Defibrillator in Advanced Chronic Heart Failure”, N Engl J Med 350(21): 2140-2150; Buxton, A. E., et al. (2000), “Electrophysiologic testing to identify patients with coronary artery disease who are at risk for sudden death. Multicenter Unsustained Tachycardia Trial Investigators (MUSTT).” N Engl J Med. 342(26): 1937-45; Cain, M. E., et al. (1996a), “Signal-Averaged Electrocardiography: ACC Consensus Document”, J Am. Coll. Cardiol. 27(1): 238-49; Calkins H., et al. (2007), Heart Rhythm 4:816-861; Chugh, S. S., et al. (2001),“Epidemiology and natural history of atrial fibrillation: clinical implications. ” J Am Coll Cardiol 37(2):371-8; Cohen, R. J. and J. M. Smith U.S. Pat. No. 4,802,491 (1989), “Method and apparatus for assessing myocardial electrical instability”; David, D. T. I. (2002), “Dual-Chamber Pacing or Ventricular Backup Pacing in Patients With an Implantable Defibrillator: The Dual Chamber and VVI Implantable Defibrillator (DAVID) Trial”, J Am Medical Association 288(No. 24): 3115-3123; Ehrlich, J. R., et al. (2008), “Atrial-selective approaches for the treatment of atrial fibrillation.” J Am Coll Cardiol 51(8): 787-92; Faddis, M. N., et al. (1999), “A Decrease in Approximate Entropy Predicts The Onset of Atrial Fibrillation” [abstract], Pacing and Clinical Electrophysiology 22(4 (part II)): 358; Franz, M. R., et al. (1988a). “Cycle length dependence of human action potential duration in vivo. Effects of single extrastimuli, sudden sustained rate acceleration and deceleration, and different steady-state frequencies”, J Clin Invest 82(3): 972-979; Frustaci, A., et al. (1997), “Histological Substrate of Atrial Biopsies in Patients With Lone Atrial Fibrillation.” Circulation 96(4): 1180-1184; Gold, M. R., et al. (2000a). “A Comparison of T Wave Alternans, Signal Averaged Electrocardiography and Programmed Ventricular Stimulation for Arrhythmia Risk Stratification.” J. Am. Coll. Cardiol. 36: 2247-2253; Gong et al. (2007) Circulation 115: 2092-2102. [0050] Hao, S., D. Christini, et al. (2004), “Effect of beta-adrenergic blockade on dynamic electrical restitution in vivo”, Am J Physiol Heart Circ Physiol 287(1): H390-4; Kalb, S., et al. (2004). “The restitution portrait: a new method for investigating rate-dependent restitution”, J Cardiovasc Electrophysiol 15(6): 698-709. [0052] Kleiger, R. E., P. Millar, et al. (1987). “Decreased heart rate variability and its association with increased mortality after acute myocardial infarction”, Am. J Cardiol. 59: 256-262. [0053] Klein, M., S. J. Evans, et al. (1995). “Use of P-wave triggered, P-wave signal-averaged electrocardiogram to predict atrial fibrillation after coronary bypass surgery.” Am. Heart J. 129(5): 895-901; Kuo, C.-S., et al. (1983), “Characteristics and possible mechanism of ventricular arrhythmia dependent on the dispersion of action potential durations”, Circulation 67: 1356-1367; Laurita, K. R. and D. S. Rosenbaum (2008), “Mechanisms and potential therapeutic targets for ventricular arrhythmias associated with impaired cardiac calcium cycling.” J Mol Cell Cardiol 44(1): 31-43; LeClercq, C., F. Victor, et al. (2000), “Comparative effects of permanent biventricular pacing for refractory heart failure in patients with stable sinus rhythm or chronic atrial fibrillation”, The American Journal of Cardiology 85(9): 1154-1156; Marrouche, et al. (2002), “Nonexcitatory stimulus delivery improves left ventricular function in hearts with left bundle branch block”, J Cardiovasc Electrophysiol 13(7): 691-5; Meisel, E., et al. (2001), “Investigation of coronary venous anatomy by retrograde venography in patients with malignant ventricular tachycardia”, Circulation 104(4): 442-447; Morton, J. B., et al. (2002a), “Sensitivity and specificity of concealed entrainment for the identification of a critical isthmus in the atrium: relationship to rate, anatomic location and antidromic penetration”, J Am Coll Cardiol 39(5): 896-906; Myerburg, R. J. and A. Castellanos (2006), “Emerging paradigms of the epidemiology and demographics of sudden cardiac arrest”, Heart Rhythm 3(2): 235-239; Narayan, S. M. (2006a), “T-Wave Alternans and The Susceptibility to Ventricular Arrhythmias: State of the Art Paper”, J Am Coll Cardiol 47(2): 269-281; Narayan, S. M., et al. (2002b), “Alternans Of Atrial Action Potentials As A Precursor Of Atrial Fibrillation”, Circulation 106:1968-1973; Narayan, S. M., et al., “T-wave alternans, Restitution of Ventricular action potential duration and outcome”, J Am Coll Cardiol 2007; 50: 2385-2392; Narayan, S. M., et al. (1999d), “Demonstrating the Pro-arrhythmic Preconditioning of Single Premature Extrastimuli Using the Magnitude, Phase and Temporal Distribution of Repolarization Alternans”, Circulation 100: 1887-1893; Narayan, S. M. and J. M. Smith (1999b), “Spectral Analysis of Periodic Fluctuations in ECG Repolarization”, IEEE Transactions in Biomedical Engineering 46(2): 203-212; Narayan, S. M. and J. M. Smith (2000c), “Exploiting Rate Hysteresis in Repolarization Alternans to Optimize the Sensitivity and Specificity for Ventricular Tachycardia”, J. Am. Coll. Cardiol. 35(5): 1485-1492; Patterson, E., et al. (2005). “Triggered firing in pulmonary veins initiated by in vitro autonomic nerve stimulation”, Heart Rhythm 2(6): 624-31; Poole-Wilson, P. A., K. Swedberg, et al. (2003), “Comparison of carvedilol and metoprolol on clinical outcomes in patients with chronic heart failure in the Carvedilol Or Metoprolol European Trial (COMET): randomised controlled trial”, The Lancet 362(9377): 7-13; Robertson, R. M. (2000, “Sudden Death from Cardiac Arrest—Improving the Odds”, N Engl J Med 343(17): 1259-1260; Rosenbaum, D. S., et al. (1994), “Electrical alternans and vulnerability to ventricular arrhythmias”, N Engl J Med 330(4): 235-41; Schauerte, P., et al. (2000a), “Transvenous Parasympathetic Nerve stimulation in the Inferior Vena Cava and Atrioventricular Conduction”, J. Cardiovascular Electrophysiol. 11(1): 64-69; Scherlag, B. J., et al. (2005), “Electrical Stimulation to Identify Neural Elements on the Heart: Their Role in Atrial Fibrillation”, Journal of Interventional Cardiac Electrophysiology 13(0):37-42; Schmidt, A., et al. (2007), “Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction”, Circulation 115(15): 2006-14; Schmidt, G., et al. (1999), “Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardial infarction”, Lancet 353: 1390-1396; Smith, J. M., et al. (1988a), “Electrical Alternans and cardiac electrical instability”, Circulation 77(1):110-21; Stambler, B. S. and K. A. Ellenbogen (1996b), “Elucidating the Mechanisms of Atrial Flutter Cycle Length Variability Using Power Spectral Analysis Techniques”, Circulation 94(10): 2515-2525; Stein, P. K., et al. (2005), “Traditional and Nonlinear Heart Rate Variability Are Each Independently Associated with Mortality after Myocardial Infarction”, Journal of Cardiovascular Electrophysiology 16(1): 13-20; Steinberg, J. S., et al. (1994), “Use of the signal-averaged electrocardiogram for predicting inducible ventricular tachycardia in patients with unexplained syncope. Relationship to clinical variables in a multivariate analysis”, J. Am. Coll. Card. 23: 99; Steinberg, J. S., et al. (1993a), “The value of the P-wave signal-averaged electrocardiogram for predicting atrial fibrillation after cardiac surgery”, Circulation 88:2618; Stevenson, W. G., et al. (1993), “Identification of reentry circuit sites during catheter mapping and radiofrequency ablation of ventricular tachycardia late after myocardial infarction”, Circulation 88: 1647-1670; Therkelsen, S., et al. (2004), “Atrial Volume and ANP in Persistent Atrial Fibrillation—Before and After Cardioversion” (abstract), Circulation 110(17 Suppl); Thomas, L., et al. (2002), “Compensatory changes in atrial volumes with normal aging: is atrial enlargement inevitable?”, Journal of the American College of Cardiology 40(9):1630-1635; Wachtell, K., M. Lehto, et al. (2005), “Angiotensin II receptor blockade reduces new-onset atrial fibrillation and subsequent stroke compared to atenolol: The Losartan Intervention For End point reduction in hypertension (LIFE) study”, Journal of the American College of Cardiology 45(5): 712-719; Walker, et al. (2003), “Hysteresis Effect Implicates Calcium Cycling as a Mechanism of Repolarization Alternans”, Circulation 108(21): 2704-2709; Watanabe, K., et al. (1980), “Computer Analysis of the Exercise ECG: A Review”, Prog. Cardiovasc. Dis. 22(6): 423-446; Weiss, J. N., et al. (2006). “From Pulsus to Pulseless: The Saga of Cardiac Alternans (Review)”, Circ Res 98: 1244; Xu, W., et al. (2002), “New Bayesian Discriminator for Detection of Atrial Tachyarrhythmias”, Circulation 105: 1472-1479; Zagrodzky, J. D., et al. (2001), “Biventricular pacing decreases the inducibility of ventricular tachycardia in patients with ischemic cardiomyopathy”, Am J Cardiol 87(10): 1208-1210.